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1966 Optimal foraging based on time and energy
CHAPTER TWENTY SIX
1966 Optimal foraging based on time and energy The concept If simple assumptions are made about the time a forager spends traveling, searching for food and the relative intake of energy, then predictions can be made about the breadth of a forager’s diet, and when it should move to a new patch to seek food. These predictions assume that natural selection will favor those genotypes that optimize energy intake and that behaviors will reflect this optimization.
The explanation There was a pervasive idea in evolutionary ecology that Fisher’s Fundamental Theorem of Natural Selection (Chapter 5) could be used as a guide to the outcome of the evolutionary process. Thus, if natural selection carries a population to a local maximum in mean fitness, then a trait like foraging behavior should evolve to maximize fitness by maximizing energy intake. This assumption is not often stated explicitly. For instance, in their study of the optimal use of patches, MacArthur and Pianka (1966) state that “Hopefully, natural selection will often have achieved such optimal allocation of time and energy expenditures, but such ‘optimum theories’ are hypotheses for testing rather than anything certain”. There is less tentativeness in Charnov (1976) when he simply says, “The predator is assumed to make decisions so as to maximize the net rate of energy intake during a foraging bout”. I will return to these issues later. MacArthur and Pianka (1966) explored the conditions under which a forager would add additional items to its diet or additional patches to its regular search routine. Their method for exploring these problems was simple, “The basic procedure for determining optimal utilization of time or energy budgets is very simple: an activity should be enlarged as long as the resulting gain in time spent per unit food exceeds the loss” (MacArthur and Pianka, 1966). To determine the optimal diet breadth MacArthur and Pianka compared the time spent searching (which should decline as you add Conceptual Breakthroughs in Evolutionary Ecology ISBN: 978-0-12-816013-8 https://doi.org/10.1016/B978-0-12-816013-8.00026-0
© 2020 Elsevier Inc. All rights reserved.
57
j
58
Conceptual Breakthroughs in Evolutionary Ecology
more items to your diet) to the time spent pursuing the item. This last factor assumes we are dealing with a predator and it assumes that more difficult-tocatch prey are added to the diet last. In the case of adding more patches, MacArthur and Pianka compare the change in hunting time per food item (by adding an additional patch to their search routine) to the change in search time per item by adding this additional patch. Charnov (1976) focused on the problem of when a forager decides to leave the patch in which it is currently feeding. Charnov assumed that the amount of energy a forager can extract from a patch will level off as it depletes food. But leaving a patch entails an energy cost (so should not be done hastily). Charnov comes up with the simple rule that “The predator should leave the patch it is presently in when the marginal capture rate in the patch (vg=vT ) drops to the average capture rate for the habitat”. Evolutionary biologists have struggled with the utility and role of optimization models (see Chapter 8 in Oster and Wilson, 1978 for a good discussion). Even if we allow that foraging efficiency is equivalent to fitness, we know that fitness is not always maximized. Kojima and Kelleher (1961) and Moran (1964) showed that population mean fitness may actually decline in two-locus selection models. This result was generalized by Karlin (1975) who showed that any two-locus model with a stable polymorphic equilibrium and linkage disequilibrium will not be at a local fitness maximum. Putting the issue of fitness maximization aside there is still the issue of assuming that natural selection could optimize foraging behavior independent of other life history traits. Indeed, some experiments have shown this is not the case. Fruit flies kept under crowded conditions, where food is limiting, evolve to become less efficient at turning food into biomass rather than becoming more efficient as might be expected under an optimization view of evolution (Mueller, 1990; Joshi and Mueller, 1996). In the case of fruit flies, adaptation to crowding also involves frequency-dependent selection for increased competitive ability which is negatively correlated with efficiency of food use. Oster and Wilson (1978) suggest that optimization theory is no more than a tactical tool for making educated guesses about evolution. However, they envision the experimental evolutionary biologist as the key in testing and rejecting theories with the classic strong-inference paradigm (Platt, 1964). But the role of the experimental evolutionary biologist is even more challenging since it is likely that many optimization models with the proper “tuning” can make essentially identical predictions. Designing critical experiments to sort through these is then the real challenge.
1966 Optimal foraging based on time and energy
59
Impact: 9 MacArthur, Pianka, and Charnov started a new way of investigating the behavior of animals which continues to this day.
References Charnov, E.L., 1976. Optimal foraging: the marginal value theorem. Theor. Popul. Biol. 9, 129e136. Joshi, A., Mueller, L.D., 1996. Density-dependent natural selection in Drosophila: trade-offs between larval food acquisition and utilization. Evol. Ecol. 10, 463e474. Karlin, S., 1975. General two-locus selection models: some objectives, results and interpretations. Theor. Popul. Biol. 7, 364e398. Kojima, K., Kelleher, T.M., 1961. Changes of mean fitness in random mating populatinos when epistasis and linkage are present. Genetics 46, 527e540. MacArthur, R.H., Pianka, E.R., 1966. On optimal use of a patchy environment. Am. Nat. 100, 603e609. Mueller, L.D., 1990. Density-dependent natural selection does not increase efficiency. Evol. Ecol. 4, 290e297. Moran, P.A.P., 1964. On the nonexistence of adaptive topographies. Ann. Hum. Genet. 21, 383e393. Oster, G.W., Wilson, E.O., 1978. Social insects. In: Monographs in Population Biology, vol. 12. Princeton Univ. Press, Princeton, N. J. Platt, J.R., 1964. Strong inference. Science 146, 347e353.
1966 Optimal foraging based on time and energy The concept If simple assumptions are made about the time a forager spends traveling, searching for food and the relative intake of energy, then predictions can be made about the breadth of a forager’s diet, and when it should move to a new patch to seek food. These predictions assume that natural selection will favor those genotypes that optimize energy intake and that behaviors will reflect this optimization.
The explanation There was a pervasive idea in evolutionary ecology that Fisher’s Fundamental Theorem of Natural Selection (Chapter 5) could be used as a guide to the outcome of the evolutionary process. Thus, if natural selection carries a population to a local maximum in mean fitness, then a trait like foraging behavior should evolve to maximize fitness by maximizing energy intake. This assumption is not often stated explicitly. For instance, in their study of the optimal use of patches, MacArthur and Pianka (1966) state that “Hopefully, natural selection will often have achieved such optimal allocation of time and energy expenditures, but such ‘optimum theories’ are hypotheses for testing rather than anything certain”. There is less tentativeness in Charnov (1976) when he simply says, “The predator is assumed to make decisions so as to maximize the net rate of energy intake during a foraging bout”. I will return to these issues later. MacArthur and Pianka (1966) explored the conditions under which a forager would add additional items to its diet or additional patches to its regular search routine. Their method for exploring these problems was simple, “The basic procedure for determining optimal utilization of time or energy budgets is very simple: an activity should be enlarged as long as the resulting gain in time spent per unit food exceeds the loss” (MacArthur and Pianka, 1966). To determine the optimal diet breadth MacArthur and Pianka compared the time spent searching (which should decline as you add Conceptual Breakthroughs in Evolutionary Ecology ISBN: 978-0-12-816013-8 https://doi.org/10.1016/B978-0-12-816013-8.00026-0
© 2020 Elsevier Inc. All rights reserved.
57
j
58
Conceptual Breakthroughs in Evolutionary Ecology
more items to your diet) to the time spent pursuing the item. This last factor assumes we are dealing with a predator and it assumes that more difficult-tocatch prey are added to the diet last. In the case of adding more patches, MacArthur and Pianka compare the change in hunting time per food item (by adding an additional patch to their search routine) to the change in search time per item by adding this additional patch. Charnov (1976) focused on the problem of when a forager decides to leave the patch in which it is currently feeding. Charnov assumed that the amount of energy a forager can extract from a patch will level off as it depletes food. But leaving a patch entails an energy cost (so should not be done hastily). Charnov comes up with the simple rule that “The predator should leave the patch it is presently in when the marginal capture rate in the patch (vg=vT ) drops to the average capture rate for the habitat”. Evolutionary biologists have struggled with the utility and role of optimization models (see Chapter 8 in Oster and Wilson, 1978 for a good discussion). Even if we allow that foraging efficiency is equivalent to fitness, we know that fitness is not always maximized. Kojima and Kelleher (1961) and Moran (1964) showed that population mean fitness may actually decline in two-locus selection models. This result was generalized by Karlin (1975) who showed that any two-locus model with a stable polymorphic equilibrium and linkage disequilibrium will not be at a local fitness maximum. Putting the issue of fitness maximization aside there is still the issue of assuming that natural selection could optimize foraging behavior independent of other life history traits. Indeed, some experiments have shown this is not the case. Fruit flies kept under crowded conditions, where food is limiting, evolve to become less efficient at turning food into biomass rather than becoming more efficient as might be expected under an optimization view of evolution (Mueller, 1990; Joshi and Mueller, 1996). In the case of fruit flies, adaptation to crowding also involves frequency-dependent selection for increased competitive ability which is negatively correlated with efficiency of food use. Oster and Wilson (1978) suggest that optimization theory is no more than a tactical tool for making educated guesses about evolution. However, they envision the experimental evolutionary biologist as the key in testing and rejecting theories with the classic strong-inference paradigm (Platt, 1964). But the role of the experimental evolutionary biologist is even more challenging since it is likely that many optimization models with the proper “tuning” can make essentially identical predictions. Designing critical experiments to sort through these is then the real challenge.
1966 Optimal foraging based on time and energy
59
Impact: 9 MacArthur, Pianka, and Charnov started a new way of investigating the behavior of animals which continues to this day.
References Charnov, E.L., 1976. Optimal foraging: the marginal value theorem. Theor. Popul. Biol. 9, 129e136. Joshi, A., Mueller, L.D., 1996. Density-dependent natural selection in Drosophila: trade-offs between larval food acquisition and utilization. Evol. Ecol. 10, 463e474. Karlin, S., 1975. General two-locus selection models: some objectives, results and interpretations. Theor. Popul. Biol. 7, 364e398. Kojima, K., Kelleher, T.M., 1961. Changes of mean fitness in random mating populatinos when epistasis and linkage are present. Genetics 46, 527e540. MacArthur, R.H., Pianka, E.R., 1966. On optimal use of a patchy environment. Am. Nat. 100, 603e609. Mueller, L.D., 1990. Density-dependent natural selection does not increase efficiency. Evol. Ecol. 4, 290e297. Moran, P.A.P., 1964. On the nonexistence of adaptive topographies. Ann. Hum. Genet. 21, 383e393. Oster, G.W., Wilson, E.O., 1978. Social insects. In: Monographs in Population Biology, vol. 12. Princeton Univ. Press, Princeton, N. J. Platt, J.R., 1964. Strong inference. Science 146, 347e353.